class_docstr: Class for a random batch method. The first element of the batch is selected by optimizing the acquisition in a standard way. The remaining elements are
  selected uniformly random in the domain of the objective.
  
  :param acquisition: acquisition function to be used to compute the batch.
  :param batch size: the number of elements in the batch.
code: def compute_batch_without_duplicate_logic(self, context_manager=None):
      x, anchor_points = (
          self.initialize_batch(),
          self.get_anchor_points(),
      )
  
      return np.vstack((x, anchor_points[: (self.batch_size - 1), :]))
  
file_path: GPyOpt/GPyOpt/core/evaluators/batch_random.py
imports: from .base import SamplingBasedBatchEvaluator
  from ...optimization.anchor_points_generator import RandomAnchorPointsGenerator
  import numpy
label_desc: Use image node_id 5 for calling the RandomBatch obj's underlying member method code with example usage: obj.compute_batch_without_duplicate_logic(context_manager) and returns: np